Google® has demonstrated that searching for information about any subject is most natural and convenient when you are allowed to simply type what you are looking for into a single input box. Prior attempts at searching the Internet for specific information included an attempt to create comprehensive categories with the user making selections from the top level category down. In Google®, typing “Shaquille O'Neil Boston Game Last Night” produces links to other websites such as ESPN.com or NBA.com where the user must then drill down using those websites' navigation systems to locate Shaq's stats for the game in question together with possibly pre-produced generic highlight video of the game in question. With ESPN.com and NBA.com, the user must navigate to O'Neil's personal page and/or the game he may have played the previous night. Each navigation attempt requires several mouse clicks and significant user interaction while reading the individual website's navigation systems. This level of interaction is excessive for topics and situations that can be handled in a more efficient and convenient way. A sports fan has a good idea of the content he/she wants to investigate, yet there are no easy search tools to allow him/her to get corresponding statistical and other contextual results (such as video links). Efforts to do so result in major compromises, moving the experience away from what feels natural and easy. With existing systems of search, fans can have difficulty pinpointing the content they want to find and will therefore reduce frustration by engaging in fewer searches than if a more convenient method was available. Users need a system that enables them to “follow their nose” as regards their unique ideas on the statistics they want to investigate. Their only alternative is to use slow and inconvenient search methods to navigate to basic standard tables and basic short highlight video reels provided by today's Internet resources.
There are no known solutions to this problem. When a user enters “Boston Celtics” into a search box, links are provided to websites that may or may not contain the information the user is looking for. They might be directed to a selection of team web pages for the Celtics and if users want to see video of a specific situation, their only choices are to navigate to generic highlight video reels or to spend a great deal of time scanning full-game video on demand (VOD) streaming to find what they want. If the user is interested in detailed information on narrow search topic such as Paul Pierce versus Kobe Bryant in last night's game and how they compared statistically together with only video clips showing the two men playing against each other, users may be able to find what they want after a great deal of time and effort. The ultimate results will be diffuse and very likely unsatisfactory, however. Currently employed solutions require direct intervention on the search engine side and are gross attempts at satisfying the deep search desires of fans wanting to obtain more specific information relating to their current interests when conducting sports-related searches.
Existing search engines impose requirements on users to conceive their own search terms. Using the fabricated search terms, the search system's back-end attempts to map these criteria into a systematic ontological-style search to produce appropriate specific targeted responses. It is not currently possible to engage in an ontological search, as that would require both the user and the system to reach consensus within the tremendous depth and scope of the English language as to the relevance and importance of the current search and how also to optimally utilize all available variations to produce desired results.
Furthermore, current search engine processes are severely limited by its “single query step” nature. The user enters a single string of words hoping to obtain results they have in mind and the search system might provide some type-ahead options to select from (if desired). When the user hits enter on their submitted word string or selects a type-ahead option, they are provided a list of possible websites that could match their needs. The user selects one of the web sites to see if there is anything of interest. Each returned web site contains a limited set of data that may or may not address the needs of the investigation in progress. Typically, the user must navigate to several websites to grow the data set, but since the data exist in several different locations, the process is ad hoc at best. The user does have the option to revise search criteria, however, but even if the new search provides better website link options, the user still faces the challenge of accessing several sites and must also use some means to aggregate data from the various sites to address their specific needs.